22 citations · 91 across the 35 of their papers we have counts for
5 papers · 1 filter
Quantifying the Carbon Reduction of DAG Workloads: A Job Shop Scheduling Perspective
Roozbeh Bostandoost, Adam Lechowicz, Walid A. Hanafy +2
Carbon-aware schedulers aim to reduce the operational carbon footprint of data centers by running flexible workloads during periods of low carbon intensity. Most schedulers treat w…
A Performance Analyzer for a Public Cloud's ML-Augmented VM Allocator
Roozbeh Bostandoost, Pooria Namyar, Siva Kesava Reddy Kakarla +8
Cloud operators increasingly deploy multiple ML models in their VM allocation pipelines. In such settings, individually benign predictions can shift and compound, severely degradin…
Carbon- and Precedence-Aware Scheduling for Data Processing Clusters
Adam Lechowicz, Rohan Shenoy, Noman Bashir +3
As large-scale data processing workloads continue to grow, their carbon footprint raises concerns. Prior research on carbon-aware schedulers has focused on shifting computation to…
LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain Demand
Roozbeh Bostandoost, Adam Lechowicz, Walid A. Hanafy +3
Motivated by an imperative to reduce the carbon emissions of cloud data centers, this paper studies the online carbon-aware resource scaling problem with unknown job lengths (OCSU)…
The War of the Efficiencies: Understanding the Tension between Carbon and Energy Optimization
Walid A. Hanafy, Roozbeh Bostandoost, Noman Bashir +3
Major innovations in computing have been driven by scaling up computing infrastructure, while aggressively optimizing operating costs. The result is a network of worldwide datacent…